Format

Send to

Choose Destination
J Proteome Res. 2017 Aug 4;16(8):3102-3112. doi: 10.1021/acs.jproteome.7b00363. Epub 2017 Jul 7.

NetProt: Complex-based Feature Selection.

Goh WWB1,2,3, Wong L3,4.

Author information

1
School of Pharmaceutical Science and Technology, Tianjin University , 92 Weijin Road, Tianjin 300072, China.
2
School of Biological Sciences, Nanyang Technological University , 60 Nanyang Drive, Singapore 637551.
3
Department of Computer Science, National University of Singapore , 13 Computing Drive, Singapore 117417.
4
Department of Pathology, National University of Singapore , 5 Lower Kent Ridge Road, Singapore 119074.

Abstract

Protein complex-based feature selection (PCBFS) provides unparalleled reproducibility with high phenotypic relevance on proteomics data. Currently, there are five PCBFS paradigms, but not all representative methods have been implemented or made readily available. To allow general users to take advantage of these methods, we developed the R-package NetProt, which provides implementations of representative feature-selection methods. NetProt also provides methods for generating simulated differential data and generating pseudocomplexes for complex-based performance benchmarking. The NetProt open source R package is available for download from https://github.com/gohwils/NetProt/releases/ , and online documentation is available at http://rpubs.com/gohwils/204259 .

KEYWORDS:

bioinformatics; feature-selection; networks; proteomics

PMID:
28664733
DOI:
10.1021/acs.jproteome.7b00363
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for American Chemical Society
Loading ...
Support Center